Musical parody, i.e. the act of changing the lyrics of an existing and very well-known song, is a commonly used technique for creating catchy advertising tunes and for mocking people or events. Here we describe a system for automatically producing a musical parody, starting from a corpus of songs. The system can automatically identify characterizing words and concepts related to a novel text, which are taken from the daily news. These concepts are then used as seeds to appropriately replace part of the original lyrics of a song, using metrical, rhyming and lexical constraints. Finally, the parody can be sung with a singing speech synthesizer, with no intervention from the user.

To sing like a mockingbird / Gatti, Lorenzo; Ozbal, Gozde; Stock, Oliviero; Strapparava, Carlo. - 2:(2017), pp. 298-304. ((Intervento presentato al convegno EACL 2017 tenutosi a Valencia, Spain nel April 3-7, 2017.

To sing like a mockingbird

Gatti, Lorenzo;Ozbal, Gozde;Stock, Oliviero;Strapparava, Carlo
2017

Abstract

Musical parody, i.e. the act of changing the lyrics of an existing and very well-known song, is a commonly used technique for creating catchy advertising tunes and for mocking people or events. Here we describe a system for automatically producing a musical parody, starting from a corpus of songs. The system can automatically identify characterizing words and concepts related to a novel text, which are taken from the daily news. These concepts are then used as seeds to appropriately replace part of the original lyrics of a song, using metrical, rhyming and lexical constraints. Finally, the parody can be sung with a singing speech synthesizer, with no intervention from the user.
15th Conference of the European Chapter of the Association for Computational Linguistics: Proceedings of Conference - volume 2: Short Papers
Stroudsburg, PA, USA
Association for Computational Linguistics (ACL)
978-1-945626-35-7
Gatti, Lorenzo; Ozbal, Gozde; Stock, Oliviero; Strapparava, Carlo
To sing like a mockingbird / Gatti, Lorenzo; Ozbal, Gozde; Stock, Oliviero; Strapparava, Carlo. - 2:(2017), pp. 298-304. ((Intervento presentato al convegno EACL 2017 tenutosi a Valencia, Spain nel April 3-7, 2017.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/198550
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